code: def test_cdf_quantile_consistency(
      batch_shape: Tuple,
      num_pieces: int,
      list_qk_x: List[float],
      num_samples: int,
      atol: float,
  ):
      distr_out = ISQFOutput(num_pieces, list_qk_x)
  
      args_proj = distr_out.get_args_proj()
      args_proj.initialize()
  
      net_out = mx.nd.random.normal(shape=(*batch_shape, 30))
      args = args_proj(net_out)
      distr = distr_out.distribution(args)
  
      alpha = mx.nd.random_uniform(shape=batch_shape)
      alpha_estimate = distr.cdf(distr.quantile_internal(alpha))
  
      assert mx.nd.max(mx.nd.abs(alpha_estimate - alpha)) < atol
  
      y = mx.nd.random_normal(shape=batch_shape)
      y_approx = distr.quantile_internal(distr.cdf(y))
  
      assert mx.nd.max(mx.nd.abs(y_approx - y)) < atol
  
file_path: gluonts/test/mx/distribution/test_isqf.py
imports: from typing import List, Tuple
  import mxnet
  import numpy
  import pytest
  from gluonts.core.serde import dump_json, load_json
  from gluonts.mx.distribution import ISQF, ISQFOutput
label_desc: Use image node_id 3 for calling a global function with example usage: test_cdf_quantile_consistency(batch_shape, num_pieces, list_qk_x, num_samples, atol) without return types